Are you a Data Engineer with strong DBT experience looking to work on large-scale, high-impact data platforms
We are looking for a modern data engineer who operates in a cloud-native, data-as-code environment built on AWS, with a focus on scalable and real-time data processing.
The ideal candidate has hands-on experience with DBT for transformations, Apache Airflow for orchestration, and Python for building production-grade data pipelines. Experience with modern streaming technologies such as Kafka, Spark, or Flink is a strong advantage.
This role suits engineers who think like software developers—comfortable with version control, CI/CD, testing, and distributed systems—rather than traditional ETL or legacy data warehouse practitioners.
Work Setup
- Hybrid: 2x onsite per week
- Office Location: Mandaluyong (Rockwell Business Center, Sheridan)
- Schedule: Monday to Friday, 10:00 AM to 7:00 PM
What You'll Do
- Design, build, and maintain scalable data pipelines integrating internal and external data sources
- Develop batch and real-time data processing workflows
- Build, optimize, and maintain DBT models, tests, macros, and documentation
- Develop data integrations with CRM, marketing, and financial platforms
- Ensure data quality, reliability, and observability through validation and monitoring frameworks
- Build data APIs and services for internal and external consumption
- Troubleshoot and resolve production issues
- Work closely with Product, BI, Engineering, and Infrastructure teams
- Participate in code reviews and Agile ceremonies
Must-Have Qualifications
- Strong hands-on experience with DBT (models, tests, macros, documentation)(Main Qualification)
- Proven experience building and maintaining data pipelines using DBT and Apache Airflow
- Experience with streaming/real-time technologies such as Kafka, Spark, or Flink
- Strong programming skills in Python and/or Java
- Advanced SQL skills and database experience (MySQL, PostgreSQL, MongoDB, Elasticsearch)
- Experience working with AWS cloud services
- Strong understanding of modern data architectures (Data Lakes / Lakehouse)
- Experience building APIs / REST services
- Strong data modelling and data quality practices
- Excellent communication and collaboration skills
Nice to Have
- Exposure to AI-assisted development tools (Cursor, Claude)
- Experience with marketing data (campaigns, rewards, segmentation)
- Work experience under gaming or gambling industry
